Information Seeking Models Dr. Dania Bilal IS 530 Fall 2006

Information Seeking Process of finding information to fill a knowledge gap Need information to make a decision Need to learn about something Need to answer a question Need to increase own knowledge about a subject of interest Need information to fill other needs

Information Seeking User interaction with IRs and sources to negotiate information need: Consult a professional human intermediary User mediation/reference process Consult friends, colleagues, classmates Self-service

Information Seeking Models Represent how people search for information in specific environments and how they interface or interact with IRs and/or traditional sources to satisfy information needs Models vary based on what researchers investigate Commonality across user information seeking

Information Seeking Models Kuhlthau’s Information Search Process Model Ellis’ Behavioral Model Marchionini’s Information Process Model Wilson’s Problem-Solving Model Belkin’s Anomalous State of Knowledge (ASK) Bate’s Berrypicking model

Kuhlthau’s ISP Model Information Search Process model (ISP) Based on five studies in naturalistic settings Emphasis on user thoughts, feelings, and actions rather than on systems Undergraduate students; validated with high school students

Kuhlthau’s ISP Model Information search process from the user’s perspectives Six stages: 1. Task initiation 2. Topic selection 3. Prefocus exploration 4. Focus formulation 5. Information collection 6. Search closure See Kuhlthau’s 2004 article, pp. 44-50.

Ellis’ Behavioral Model David Ellis describes 8 information seeking patterns of social scientists, physical scientists, and engineers in using hypertext (e.g., the Web). Starting (Surveying) Chaining Monitoring Browsing Differentiating (Distinguishing) Filtering Extracting Verifying Ending

Ellis’ Model See D. Turnball, 2.1.1.1-2.1.1.2.

Marchionini’s Model Problem solving approach to understanding information seeking process in the electronic environment Eight processes that may work in parallel: Problem recognition, Problem definition, Selection of system/source, Problem articulation (query formulation), Search execution, Examination of results, Extraction of desired information; Reflection, Iteration, and Stopping of search process

Wilson’s Problem-Solving Model T.D. Wilson’s 1997 model Goal-directed towards problem solving Based on a survey of research in the health field Users move from uncertainty to certainty through the problem-resolution process

Wilson’s Problem-Solving Model Stages: Problem identification Problem definition Problem resolution Solution statement Model has affective dimensions Stages are sequential and non-linear

Belkin’s ASK Theory ASK (Anomalous State of Knowledge) “The cognitive and situational aspects that were the reason for seeking information and approaching an IR system” (Saracevic, 1996). Knowledge gap (anomaly) and the need to solve it

ASK Model Definition Contributions of ASK A recognition by an individual that his/her model of some aspect of the external world and of her/her position in it with respect to some particular situation is insufficient and knowledge is needed to reduce uncertainty Contributions of ASK Reinforced the certainty of the user’s needs Recognized the iterative nature of information retrieval users return to the IR system repeatedly to satisfy their information needs Move towards system design that is user- rather than system-centered (people rather than documents)

Bate’s Berrypicking Model Marcia Bates examined the search behavior of researchers who were experts in a particular field (e.g., engineers, chemists, social scientists) Researchers do not make a single search across collections—they move across a variety of sources as follows:

Bate’s Berrypicking Model Bit-at-a-time retrieval: not a direct route from information need to final retrieved set. Searching changes direction, pauses, and meanders as the user reads retrieved documents, follows up on leads, and responds to shifts in thinking. New information gives users new ideas, new directions to pursue, and a new conception of their information needs. Researchers’ information needs and the queries they use to represent them these needs in systems are continually shifting: evolving search, dynamic, non-linear User information needs are not the same and they do change during the search process